Mental health of the adult population in Germany during the COVID-19 pandemic. Rapid Review

This rapid review examines how the mental health of adults in the general population in Germany changed during the COVID-19 pandemic. We conducted a systematic literature search and included 68 publications as of July 30 2021. The underlying studies were classified according to their suitability for representative statements for the general population and for estimating changes in mental health over time. In addition, the observation period and operationalisation of outcomes were considered. The first wave of infection and the summer plateau were mapped by 65% of the studies. Studies that were particularly suitable for representative statements due to their research design showed mixed results, which tend to indicate a largely resilient adult population with a proportion of vulnerable individuals. A predominantly negative development of mental health was described by results from more bias-prone study designs. Routine data analyses showed decreases in outpatient and especially inpatient care, increased use of a crisis service, mixed results for outpatient diagnoses, incapacity to work and mortality as well as indications of shifts in the spectrum of diagnoses. As the current evidence is ambiguous, generalised statements should be reflected in favour of a differentiated view. There is a need for research on the further course of the pandemic, specific risk groups and the prevalence of mental disorders.


Introduction
As a multidimensional stressor, the COVID-19 pandemic and the associated infection control measures pose risks to the mental health of the population at various levels [1][2][3]. The individual experience of insecurity and anxiety of an infection, the loss of protective factors for mental health (e.g. social and leisure activities, access to care services), the burden of infection protection measures [5][6][7], the loss of relatives [4] and immediate physical, neurological and psychological symptoms of a COVID-19 infection [8] can have negative consequences for mental health. Longer-term consequences [1,2] are being discussed in the event of an economic recession caused by the pandemic [9][10][11]. The increase in risk factors that already existed before the pandemic may also create additional mental health burdens, such as a higher risk of domestic violence [11][12][13] or increased loneliness [14,15] in the wake of contact restrictions and widespread closures. In principle, it can be expected that the longer the Inclusion criteria (1) Target population: General population in Germany (and subgroups according to region, age, marital status, employment) (2) Age group: Adult (3) Observation period: During the COVID-19 pandemic (4) Constructs shown: Mental health as the main outcome duration or chronification of stressors, the more difficult it becomes to cope successfully [10].
Against this background, the British Psychiatric Association predicted a 'tsunami of mental disorders' as early as May 2020 [17]. Experts also expect an increase in mental stress and disorders in Germany [3,18,19]. However, the current findings on the development of the mental health of the population during the COVID-19 pandemic are heterogeneous overall and difficult to assess due to their methodological diversity. Thus, studies from other countries as well as international reviews find, on the one hand, a (partly extreme) increase in psycho-social stress and a subsequent increase in mental disorders [20][21][22][23][24][25][26], but on the other hand, no lasting increase in psychopathology [27][28][29][30]. In addition to the inconsistency of the results of international studies, conclusions for Germany are also made difficult by significant differences between the countries in the course of the pandemic. In particular, the development of the number of cases and deaths, the resulting burden on the health care system as well as the measures taken to protect against infection, to stabilise the economy and to provide social security differed between the countries.
Since research reacted very quickly to the crisis situation, there is now both a high number of empirical studies and a large variation of the research methodology used [31]. The high demand for reliable findings as a basis for evidence-based policy decisions (e.g. to minimise risks and adapt care services) makes it understandable why rapid solutions are used for immediate data collection or prompt publication of the work on preprint servers even before the quality-assuring peer review. However, this practice makes it necessary to examine the quality and generalisability of 4 FOCUS (Annex Table 1). All texts extracted in this way were filtered for their reference to Germany using a third search string.
Offline search Given the acute need for information with a correspondingly rapid development of scientific publications as well as other dissemination formats, such as reports, study websites, press releases or reports from health insurance funds, it can be assumed that not all findings or publications on the development of mental health in the German general population during the COVID-19 pandemic are already listed in international databases. Based on this, the literature search was extended to include the following areas: (  Table 1); press releases and current reports or studies by, among others, service providers and suppliers of the health care system (e.g. health insurance funds, Central Institute for Statutory Health Insurance in Germany, hospital statistics).
(5) Publication of a temporal comparison (against measurement time points before the start of the pandemic or during the pandemic) (6) Publication language: German/English Exclusion criteria (1) Publication type: Reviews, Opinions, Comments, Letters to the Editor (2) Methodology: Qualitative data (3) Presentation of study methodology: Methodology not presented with sufficient transparency in published abstracts or on posters (4) Analysis design: Exclusively correlation analyses without reporting of frequencies or their changes in the general population. (5) Target population: Subgroups beyond the above selected sociodemographic characteristics (e.g. people with pre-existing mental disorders, health workers, students).

Systematic search
The search was based on the literature database created by the library of the Robert Koch Institute in the course of the COVID-19 pandemic (accessed 30.07.2021). Since the beginning of the pandemic, all publications identified by means of several search strings (Annex Table 1) in the PubMed and Embase databases and the additionally searched preprint servers arXiv, bioRxiv, ChemRxiv, medRxiv, Preprints.org, Research Square and Social Science Research Network (SSRN) have been entered into this database on a weekly basis. The literature database was searched for texts on mental health using two search strings defined by filter terms Journal of Health Monitoring 2021 6(S7) Mental health of the adult population in Germany during the COVID-19 pandemic. Rapid Review Journal of Health Monitoring 5 FOCUS

1) Observation periods
In order to assess the extent to which the current state of research allows statements about the entire course of the pandemic since March 2020, the observation periods of the included studies were recorded with the help of half-monthly intervals. Their distribution over the entire period was considered, irrespective of whether results were also reported for them individually. Periods were included for which data were available for at least one week from the respective halves of the month. If this was not the case for any half of the month, the study was assigned to the period in which the most study days occurred. To classify the observation periods, the development of the pandemic in Germany was divided into four phases (wave 1 to 3 and summer plateau 2020) following Schilling et al. [37] as well as Tolksdorf et al. [38] and illustrated with the case and death figures of COVID-19 ( Figure 2).
2) Study design of the data used Two criteria were used to assess the suitability of the study design of the data analysed in the publications for drawing conclusions about the development of mental health in the general population during the COVID-19 pandemic: Criteria 1: Representativeness of the data for the general population To assess the suitability of the data used in a publication for representative estimates in the general population, primary data was distinguished from routine data.
Routine data are generated in the course of standard documentation and billing in health care processes or in official statistics and represent these as a complete survey (5) Screening of bibliographies of COVID-19 related reviews, statements and policy briefs for relevant studies and publications (as of 10.06.2021) (6) Screening for relevant COVID-19 related studies and publications listed on the website of the German Society for Psychiatry, Psychotherapy, Neurology and Psychosomatics (DGPPN) (accessed 10.06.2021) [36].
Title, abstract and full text screening After piloting the procedure in the review team and excluding duplicates, the title and abstract screen was carried out by an experienced person (EM). More than 20% of the titles were additionally checked by at least one other person in the team. If the assessment of inclusion or exclusion of a publication was ambiguous, no exclusion was carried out conservatively. All remaining publications were reviewed in full text by at least two people. The publications that were ambiguous in this step were discussed in a team of three people and included or excluded in an iterative process based on the criteria mentioned above. In the course of this process, the first data extraction of the individual publications took place. Information was systematically transferred to a table created for this purpose. For individual publications, the respective data type (primary data, routine data) was identified, on the basis of which the publications were grouped.

Classification of included publications
For a meaningful summary of the findings against the background of the research methodology used and the resulting scope of the empirical results, the included publications were systematised in three ways as follows: odological study conducted before the pandemic, for example, an overrepresentation of participants with psychological problems by a factor of about 2.5 was found in such a sample [44]. In order to avoid the risk of biased estimates or to be able to assess the uncertainty of the estimates, the use of non-probability samples to study the mental health of the general population during the COVID-19 pandemic is even explicitly discouraged from a methodological point of view [45]. Nevertheless, this pragmatic form of sampling is frequently used and results of corresponding studies find their way into the scientific and public discourse. In order to enable it to be differentiated, the present review differentiated between probability and non-probability samples.
Criteria 2: Estimation of changes over time during the pandemic An essential prerequisite for a robust assessment of change over time is repeated measurement points that are identical in terms of study design (i.e. sample, survey mode, etc.) and outcome measurement. [46]. Trend studies, i.e. repeated and representative cross-sectional or panel surveys with identical study designs, are particularly suitable for this purpose [46,47]. In these studies, characteristic values collected at different points in time are compared at group level between two samples. In one-off, representative cross-sectional studies, it is possible to assess changes over time by comparing them with norm samples, other reference surveys and retrospective surveys. However, possible sources of error such as recall bias, mode effects or deviating sample composition must be included in the interpretation [48].
Representative cohort or longitudinal studies offer the possibility of identifying changes in specific population groups without sampling [39]. They are available from different data holders at different levels and thereby differ with regard to their population-based representativeness. For example, data from a single clinic or health insurance fund represent its health care provision without distortion, but may deviate from other clinics or health insurance funds as well as from the nationwide inpatient care or the entirety of persons with statutory health insurance [40].
In primary data collections, a sample of the target population is included in a study. The best approximation to an estimate representative of the general population in Germany is provided by random sampling (probability sampling). Samples can be drawn (a) from the total population with known selection probability [41] or (b) from an access panel with a stratified sampling design if necessary [41,42]. The persons drawn are invited and motivated to participate. Ideally, measures are implemented to recruit participants from hard-to-reach population groups [41]. Possible biases due to the study design (design effects) and the non-participation of certain population groups (non-response) can be identified and taken into account in the data analysis, for example with weighting factors [43]. In contrast, in studies with non-probability samples (samples without random selection), interested persons participate on their own initiative by accepting non-personalised invitations that are primarily distributed by the media [41]. Thus, participation depends, among other things, on knowing about the study, one's own motivation to participate and access to the providing medium. These samples can thus be systematically biased by selection effects in a methodologically uncontrollable way and therefore represent less reliable sources of information for the general population [41,42]. In a meth-7 FOCUS 3) Operationalisation of mental health outcomes To assess how comprehensive and valid the multi-faceted topic of mental health was captured in the included studies, the mental health outcomes were classified according to the measured construct and its operationalisation. The survey was subdivided into (a) indicators of positive mental health, (b) indicators of mental distress, (c) indicators of acute symptoms of a mental disorder and (d) indicators of health care provision and mortality.
The inventories used to measure the indicators include different possibilities for analysis and interpretation, both with regard to the construct being measured and to pandemic-related changes over time: Non-standardised items or single items of established inventories have limited validity for the measurement of the construct due to a lack of studies on reliability and validity [50]. In contrast, standardised measurement inventories are validated for a defined construct and -given a comparable study design -allow comparison with previous studies and ideally with reference values from norm samples. These also include screening instruments in which currently present symptoms of a mental disorder are queried and thus persons with a high symptom burden can be identified. The frequency of a mental disorder, as it would be diagnosed in a standardized clinical interview, can, however, be both overestimated and underestimated by screening instruments [see e.g. 51]. Documented diagnoses in the health care system (incl. in reports of incapacity for work) presuppose the utilisation of medical or psychotherapeutic services as well as the recognition and documentation of mental disorders by those providing treatment, which means that, among other things, persons with unmet treatment needs are not depicted [52][53][54]. via intra individual analyses, but can lose representativeness due to the drop out of individuals over time [47,49].
Synopsis of the criteria: Classification in study types To assess the suitability of the study methodology of the data underlying the publications for assessing temporal changes during the pandemic in the general population, a total of seven study types were defined by combining the two criteria listed above (Annex Table 2): Within the primary data studies (Category I), the studies with randomly drawn samples were divided into trend studies with random sampling from the general population (study type A) or an access panel (study type B). One-time cross-sectional surveys with random sampling were assigned to study type C, in which the comparison over time took place via retrospective queries or comparisons with other reference surveys without consideration of possible design differences. Cohort studies with random sampling in non-randomly selected regions and without sample augmentation to compensate for drop out were assigned to study type D. Primary data studies with non-probability samples were subdivided into longitudinal studies with repeatedly interviewed participants (study type E) and cross-sectional studies (study type F). Routine data (Category II) were not subdivided, as they are usually available at different points in time and -given the same coding and analysis -can be compared over time.
As comparatively reliable estimates for changes in mental health in the general population during the pandemic, study types A, B, D and, to a limited extent, C, as well as routine data can be contrasted with study types E and F, which are more susceptible to bias.

Systematic extraction of study results
The central results already extracted from the publications in a first step were prepared in tabular form according to the criteria listed here (Annex Table 3, Annex Table 4) and presented in the text. The systematised data extraction was carried out under quality assurance by at least two other independent persons in each case (Annex Table 3).

Literature search
A total of 1,843 publications relating to Germany were identified using the various search strategies (as of 30.07.2021). With the help of a multi-stage inclusion and exclusion process ( Figure 1), 68 publications were included in the review.

Classification of included studies
Observation periods At the time of the literature search, the observation periods largely referred to the time of the first wave of infection of the COVID-19 pandemic, which still had relatively low incidence and death rates of people infected with SARS-CoV-2 compared to the later waves ( Figure 2). From the second half of March onwards, more than 20 studies were available in each half of the month. For the 2020 summer plateau between the first and second waves, published data from at least 13 studies were also available. However, with the turn of the year 2020/2021, the number of studies decreased sharply: While eight to nine studies were still available in the respective halves of the month for the A variety of studies with divergent research methodologies examined the development of mental health during the COVID-19 pandemic.
second wave in 2020, there were only one to five studies for the second and third waves in 2021.
Representativeness of the sampling for the general population and the estimation of changes over time during the pandemic The review included 44 publications based on 25 primary data sources (Category I) and 24 publications based on 18 routine data sources (Category II) ( Table 1).
Among the primary data sources, a total of 16 publications from six trend studies with randomly drawn samples from the general population (study type A), five publications from two trend studies with randomly drawn samples from an access panel (study type B) and three further representative cross-sectional studies with one publication each (study type C) were identified. Two publications originated from a cohort study with a random initial sample in non-randomly selected regions (study type D). Four longitudinal studies with five publications (study type E) and nine cross-sectional studies with 13 resulting publications were based on non-probability samples.
In summary, a total of 26 publications based on 12 primary data sources were available in the study types A, B, C and D, which are considered reliable for statements with regard to the general population. In contrast, there were 18 publications from 13 studies in the study types E and F, which are more susceptible to bias. Taking all study categories into account, it became apparent that more than two thirds of all publications (50 of 68) and studies or data sources (30 of 43) could be assigned to the study types (A, B, C, D, routine data) that were assessed as reliable.  (b) Indicators of mental burden The measurement of feelings of anxiety or dejection, which are counted among the indicators of psychological stress (Annex Table 4), was mainly carried out with individual items from standardised instruments. Results were reported in six publications from three studies. COVID-19 related anxiety and distress were measured with both single-item and standardised instruments and reported in three studies with four publications. Situational distress and psychosocial stress were primarily measured with standardised instruments and reported in a total of 13 publications from eight studies.
Study types A and B consistently showed increased anxiety at the beginning of the pandemic, which decreased in all population groups during April 2020 [61,72] and subsequently remained stable until March 2021 [72] and July 2020 [59,60], respectively. In the case of dejection, the slightly increased level at the beginning of the pandemic stagnated until the end of April 2020 [74, 72] and contin-

Classification and results related to mental health outcomes
(a) Indicators of positive mental health For indicators of positive mental health, results on life satisfaction, well-being and resilience were reported from a total of eight studies in 16 publications (Annex Table 3, Annex Table 4). The measurement was carried out with individual items as well as with standardised inventories. With the exception of study type D, results are available for these indicators from all study types. For the first pandemic months, stable life satisfaction [16,62] and stable well-being [16,56,65,67] were reported on the basis of study type A until July 2020 compared to previous years. A later survey showed reduced life satisfaction [63,64] and a slightly reduced well-being for January and February 2021 [63,64]. However, the stable median values of the overall group in the first months of the pandemic concealed divergent developments in subgroups: Life satisfaction increased among people with low income or low education, but decreased among the self-employed [66] and people with high education or high income [65] and especially among women [67] as the pandemic progressed [63,64]. Well-being increased among those living alone, was unchanged among couples without children and single parents, and decreased among couples with children [62].
Similarly  [14]. For the first 20 days of the lockdown in April and November 2020, the burden remained high [90].
(c) Indicators of acute symptoms of mental disorder Of a total of 25 primary data studies, 18 used standardised screening instruments to measure acute symptoms of a mental disorder. Results were reported in 31 publications (Annex Table 3 and Annex Table 4). In addition to screening for general psychopathological symptoms, the focus was primarily on depressive and anxiety symptoms.
Either no changes or decreases in psychopathological symptoms were reported from study type A compared to pre-pandemic comparison periods, apart from one finding of higher median scores in depressive and anxiety symptoms in May to June 2020 compared to the same months in 2018 [55]. Nationwide, depressive symptoms remained unchanged in the months after the outbreak compared to the months before [57,58]. In the Mannheim region, too, no difference was detected in depressive and anxiety symptoms or somatoform disorder symptoms compared to 2018 [56]. A study with two survey periods during the pandemic (April to June 2020 [16,65,67] and January to February 2021 [63,64]) did show an increase in depressive and anxiety symptoms compared to 2019, especially at the level of incident individual symptoms [68]. However, the significantly higher value compared to 2019 was in line with the results from 2016 [16,65,67]. With regard to individual symptoms, a decrease in fatigue/lack of energy as well as concentration difficulties was described for the first lockdown in 2020 compared to the same period in 2019 [57,58]. A decrease in the median value of depressive symptoms was also ued to rise until March 2021 in the youngest age group [74]. While no increased psychosocial stress was found in study type A in the Mannheim region for May 2020 [56], it was increased in study type B in March 2020 [74] and changed over time: Anxiety declined until September 2020, increased until the end of April 2021 (especially among young adults) and declined again from May 2021 [74]. Another Type B study showed increased stress levels in February 2021 compared to the summer months of 2020 [70,71].
Parents of minor children in study type C also reported an increase in stress experience at the time of the highest stress to date compared to January 2020 [76,77].
Longitudinally, an increase in psychosocial stress was detected in study type D for May 2020 in all age groups. This was stronger in regions with higher incidence and in individuals who tested positive for COVID-19 [80]. Accordingly, in a sample of healthy adults in study type E, intra-individual daily stressors were reduced between the end of March and mid-May 2020 [81,83]. At the group level, another study of this type found a decrease in COVID-19 specific anxiety from March to June 2020, while longitudinally, an increase was found in about 10% of the sample [82].
Findings from study type F showed elevated psychological distress for almost all reported indicators, which increased over the course of the pandemic. For April to May 2020, increased anxiety [97] and COVID-19 specific fears with a subsequent decrease below the baseline level [93, 94] and a continuous increase [14] for distress were reported. Stress levels were estimated to be moderate [95] in April 2020 and very high [91,92,94] in the first months of the pandemic, remaining at a stable high [94] level until July 2020 and increasing steadily until September 2020 Stable values over time in the overall group are partly due to opposing trends in subgroups.

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of intra-individual changes consistently pointed to a group of about 8% [83] to 10% [82, 85] of the study participants who experienced an increase in psychological symptoms during the pandemic, and as many as 25% with increases in the severity of depressive symptoms [82]. Another group of 8% to 9% initially developed increased psychological symptoms, which were reduced again within a few weeks [81,83,85]. However, the majority reported stable and in some cases even improved mental health (ibid.).
From study type F, elevated levels of psychopathological symptoms were reported almost exclusively. In mid-March to mid-April 2020, the median scores for depressive and anxiety symptoms were significantly elevated in two samples compared to pre-pandemic reference samples and were interpreted as an indication of a possible increase [89]  . Immediately afterwards, the symptoms dropped again slightly, but remained at an elevated level in the further course of the pandemic until the end of July [90] and in the second lockdown in November 2020 [94]. The values were interpreted as an up to eight-fold increase observed in all population groups during the course of the pandemic from March to July 2020 [59]. Decreases were also described for psychopathological symptoms from mid-March compared to the month before (except for the elderly and persons with low-income) [69].
Results from study type C are based on comparisons with norm samples of the respective inventories and showed no changes in psychopathological symptoms for persons over 65 years of age for April 2020 compared to 2018 [75], while in the group of parents of minor children a slight increase could be found for both depressive and anxiety symptoms (retrospectively assessed for the time of subjectively highest stress) compared to 2010 [76,77].
In the trend analysis of a longitudinal study of study type D, i.e. when comparing the survey points at group level, the proportions of those with current depressive symptoms or a generalised anxiety disorder were higher in May 2020 than two to seven years earlier in the initial sample [79,80]. Longitudinally, symptoms increased among persons in the age range 18 to 60 years, but not among the elderly (ibid.). This intra-individual increase was most evident in the youngest age group (20 to 39 years) as well as in regions with a high incidence of infection and among persons tested for COVID-19 (ibid.).
In trend analyses of study type E, reduced psychopathological symptoms were found from the end of March to mid-May 2020 compared to the last measurement point . In June 2020, only these two groups of doctors showed a significant increase. Declines were also recorded in psychotherapeutic individual and group therapies as well as substitution therapy for drug addiction, which remained consistently below the 2019 level from mid-March 2020 [121].
Developments in incapacity to work due to mental disorders (IW) differed between the health insurance funds. BARMER  (d) Indicators of care patterns and mortality Results on indicators of care provision and mortality were reported in 24 publications from 18 data sources. Various parameters like the use of a crisis service (two publications from one data source), outpatient care for mental disorders (three publications from two data sources), incapacity to work due to mental disorders (nine publications from six data sources), inpatient care for mental disorders (seven publications from six data sources) and mortality in the context of mental disorders (three publications from three data sources) were evaluated.
The utilisation of the crisis helpline 'TelefonSeelsorge' at the end of March 2020 showed an increase, which declined again in the following weeks [117,118]. It particularly concerned counselling topics in the spectrum of health, relationships and violence and was higher in federal states with stricter infection control measures [118].
In outpatient mental health care, an increase in GPs' first diagnoses of anxiety disorders was reported in the period March to June 2020, affecting more people aged over 30 years and with diagnosis of asthma and COPD [106]. In contrast, a decrease was reported for outpatient first diagnoses of depression among persons aged ≥65 years, for whom physician contacts, referrals and hospital no differences can be detected between different phases of infection control measures (light vs. heavy restrictions) nor to the temporal developments of previous years [116]. In preliminary evaluations, the nationwide suicide rates show a slight decrease in cases for 2020 compared to 2019 [115].

Discussion
Given the extensive and diverse body of studies, this rapid review aims to provide a comprehensive assessment of the development of the mental health of the adult population in Germany during the COVID-19 pandemic. For this purpose, as of July 30 2021, 68 relevant publications were identified and included in the review. The data used in the publications was classified with regard to the observation period, the research methodology used to answer the research question and the content. Based on the extracted main results, the state of research is summarised in the following and further research needs are derived.
The data of 65% of the included publications referred to the first wave of infection and the summer plateau 2020. In comparison, the level of information for the second and third waves from autumn 2020 to summer 2021 is much more limited and limits a comprehensive assessment of the entire course of the pandemic.
At the present time, the primary data studies show a large variation of the research methodology used across the study types A to F as defined here. More than half of the studies conducted and slightly less than half of the publications resulting from them were accounted for by study types E and F. These do not represent reliable sources teristics: For AOK-insured persons, the number of inpatient cases in psychiatric, psychotherapeutic and psychosomatic clinics and departments fell below the 2019 level from March 2020 to February 2021 [100]. From mid-March to early April 2020, the decline in diagnoses of mental and behavioral disorders (as coded in ICD-10 chapter V) was rather high compared to other indications [98]. One hospital group also reported a decline in admissions to day clinic and inpatient admissions from mid-March to the end of May 2020 [102], which affected various main diagnosis groups to varying degrees. At the same time, the length of stay of inpatient cases with coded diagnoses of mental and behavioral disorders fell considerably in another hospital network [111]. For psychiatric emergencies, there was a decrease in presentations [111,113,114] in the period from the beginning of the pandemic to the end of May, and only one hospital found no change in the absolute number of psychiatric emergencies [112]. At the same time, an increase in repeat presentations for psychiatric emergencies and changes in diagnostic spectrum and psychopathological findings were observed, with formal thought disorder, hopelessness and social withdrawal documented more frequently, while suicidality remained unchanged [114]. Among psychiatric emergencies [114] and psychiatric consultations [112] where a substantive relationship of the complaints to the COVID-19 pandemic was identified, the proportion of persons with suicide attempts was increased compared to cases unrelated to the COVID-19 pandemic.
A change in mortality in the context of mental disorders is evident for the number of deaths due to intoxication, which was higher in 2020 than in 2019 nationwide of the year 2020/2021. The necessity of a socially differentiated approach was illustrated by findings showing that a stable population mean value is based on diametrically opposed developments in different population groups. From the more bias-prone study type F with non-probability samples, predominantly results of a negative development of mental health and a strong increase of stress were reported. However, against the background of possible selection effects [42,44,45] compared to the general population, these findings should be interpreted cautiously as indications of changes in individual subgroups that need to be identified more precisely. In longitudinal studies of type D and E, both intra-individual deterioration and improvement of mental health were observed. Again, longitudinal analyses indicated that stable scores over time in the overall group may be due to contrasting trends in subgroups. Results based on routine data analyses in the context of mental health showed predominantly decreases in outpatient and inpatient case numbers or services, increases in the use of a crisis service, mixed results for the development of outpatient diagnoses, incapacity to work and mortality, as well as indications of shifts in the diagnostic spectrum and in clinical characteristics of treated cases.
In summary, the current scientific evidence can be considered inconclusive. Taking into account the study methodology used, statements of a dramatic deterioration in the mental health of the adult population during the COVID-19 pandemic in Germany in particular should therefore be questioned in favour of a more differentiated view.
Comparable to this, the first international systematic reviews also reported a heterogeneous picture [31]. In addi-of information for the general population due to the potential bias of the results, even though they can provide valuable information through the analysis of correlations or, above all, intra-individual changes. Despite their high visibility in scientific discourse due to a relatively high number of publications, these results should be placed into context with current studies less prone to bias and thus be interpreted with caution. Compared to primary data analyses, routine data analyses also evaluated a high number of data sources, from which, however, far fewer publications emerged.
From the broad spectrum of mental health topics, the studies conducted primarily focused on indicators of a current symptoms of a mental disorder using validated screening inventories. Indicators of mental distress and positive mental health ranked second and third, respectively. No study used standardized diagnostic procedures to determine the frequency of mental disorders according to established classification systems. Consequently, no evidence-based statement can yet be made, about the development of the prevalence of mental disorders in particular.
The comparison of results across all indicators indicates dependencies on the study design: The cross-sectional study types A, B and C, which were assessed as more suitable for a reliable estimation for the general population due to a representatively designed random sample, reported predominantly mixed results. If anything, the results suggest that the adult general population was rather resilient during the study period and that their mental health remained relatively stable despite increasing stress. First included publications with more recent data collection pointed to a deterioration in life satisfaction from the turn Journal of Health Monitoring 2021 6(S7) Mental health of the adult population in Germany during the COVID-19 pandemic. Rapid Review Journal of Health Monitoring 17 FOCUS thermore, no established risk of bias tool was used, as systematic biases were explicitly considered as an object of the review question.
In principle, it should be noted that trends that already existed before the pandemic were not distinguished from temporal changes during the pandemic in most publications, neither empirically nor in the discussion of results. The latter can therefore not always be interpreted as causally linked to the pandemic.
From the present results, focal points of the current need for research can be derived: (1) For a comprehensive assessment of the course of the pandemic so far, results are needed for the second and third waves of infection. Since the increase in the number of cases and deaths as well as the (continued) duration of infection protection measures were comparatively higher during the latter, changed and increased risks for mental health can be assumed compared to the first wave, such as the chronification of stressors as well as the continued loss of resources [3]. Surveillance of the mental health of the population is also necessary after the infection waves have subsided, among other things because mental disorders can be preceded by longer sub-clinical or prodromal phases (precursor phases) and thus there may be a timedelayed increase in psychopathology [3]. In addition, it should be noted that in the past, economic recessions have been associated with an increase in mental disorders and suicides in the population, which may also contribute to an increased burden of disease in the context of a pandemic [2,9,10,124].
(2) Similar vulnerable and highly stressed groups for the development or worsening of psychopathological symp-tion to significant increases [24] and decreases [27] in psychopathological symptoms, there was a tendency for mental health problems to increase at the beginning of the pandemic, which decreased [30] almost to the initial level after a few weeks. This observation corresponds to the findings from study types A, B and C outlined for Germany. Results of opposing trends in subgroups analogous to the findings from study types A and E were also reported [122]. However, a comprehensive evaluation of the international findings, in consideration of research methodology, regional differences in the course of the pandemic and special features prior to the outbreak, is still pending.
A psychological reaction of people to a crisis as profound as the global COVID-19 pandemic is to be expected within an appropriate and healthy range of experience and behaviour. Reduced well-being, increased mental distress or partly transient (single) symptoms of mental disorders alone do not imply a need for clinical treatment compared to manifest mental disorders with long-term functional limitations [31]. Since the development of mental disorders requiring treatment is often preceded by chronic overload and stress with a longer incubation period, measures should nevertheless be taken to prevent them and to promote mental health [see e.g. 3, 123], as implied by the available research on the experience of stress.
The limitations of the present rapid review include the following aspects: As the focus was on the mental health of the general population, studies in specific populations such as students, people with mental disorders or health workers were not included. Not all sources of potential bias were considered in the classification of included studies (e.g. survey mode, response or drop-out rates [41]). Fur-18 FOCUS (5) Finally, the direct effects of contracting COVID-19 or requiring intensive medical treatment [129, 130] may also have a negative impact on mental health and may be reflected in changes at the population level in the short or long term, especially against the background of higher case numbers during the later waves of infection. Consequently, population-based studies should capture these two events where possible and take them into account when examining mental health trends.
In the coming months, the publication of further research results on mental health in Germany during the COVID-19 pandemic can be expected. Since methodologically high-quality studies in particular require a longer planning phase, the longer the pandemic lasts, the greater the number of studies that allow valid statements at the population level as well as over time and that contribute to closing some of the research gaps mentioned. For effective mental health surveillance, study results must be systematically pooled and comparatively evaluated on an ongoing basis. Knowledge of the current situation and the temporal development dynamics of mental health in Germany can contribute to actors from health promotion, prevention, care and relevant political departments developing targeted and evidence-based approaches in order to manage the COVID-19 pandemic.
toms are described across all study designs and also across countries. In addition to people with mental disorders and health workers, these include young people, women and families with young children. International reviews also point to a widening of social inequalities in mental health in the wake of the pandemic by education, insecure income or unemployment [125]. The systematic identification of risk groups in Germany could take place in a second step on the basis of the present research. It is necessary for target group-oriented health promotion, prevention and care planning and could be included in future pandemic and crisis management.
(3) Internationally, too, it is demanded that studies whose design allows a reliable and differentiated assessment of temporal changes in the general population should be carried out as a matter of priority [45,126]. Trend and cohort studies in particular can contribute to the identification of subgroups that are particularly affected or at risk and test previous indications of the reversibility of negative effects as well as favourable factors. The results should be reported in a socially stratified manner in order to uncover possibly opposing developments in different population groups.
(4) Research gaps remain for a variety of aspects of mental health, including key indicators such as incidence and prevalence of mental disorders and functional limitations, burden of disease and mortality associated with mental distress and disorders. While the standardised diagnosis of mental disorders before the pandemic showed a stable prevalence in the population (survey 1997-1999 vs. 2009-2012 [127, 128]), the assessment of current changes in care needs requires a renewed psycho-diagnostic data collection.
The German version of the article is available at: www.rki.de/journalhealthmonitoring Funding The review was carried out within the framework of the project 'Establishment of a national Mental Health Surveillance at the RKI (MHS)', which is funded by the German Federal Ministry of Health (Chapter 1504 Title 54401, Duration 03/2019-12/2021).

Conflicts of interest
The authors declared no conflicts of interest.     (2)

Category I: Primary data
Abbreviations used: M = median, SD = standard deviation, cut-off = fixed limit of an instrument from which a certain interpretation of the results applies, n = sample size, N = full survey, OP = observation period, CP = comparison period, t1 = measurement time 1, t2 = measurement time 2., difference = calculation of the intra-individual deviation of different measurement times

Description and interpretation by authors of the publication Data basis: SOEP-CoV
Survey study (telephone): special study with two survey waves of the Socio-Economic Panel (SOEP) based on offline random sampling (households of the general population, persons aged 18-over 80); comparison over time between the samples and additionally with identically surveyed outcomes in previous years' SOEP surveys. Reduction among self-employed [4]; especially reduction among women [5] also in further course of the pandemic [13,14] Increase for single people; unchanged among couples without children and single parents; reduction for couples with children [1] Increase among people with low income, low education; decrease among people with high income, high education -reduction of socioeconomic differences [3], is also evident as the pandemic continues [13]  Increase of incidence of depressive symptoms in general population compared to 2019: 21% depressive symptoms not present at any time in OP vs. 38% in CP [6] Particularly affected by an increase are people with a migration background [3,13,14], women and younger people [13,14]; longitudinally, the situation worsened considerably for female self-employed workers [6] Continued on next page

Outcome
Operationalisation/ measuring instrument from week 5: Two items [7,8] Decrease of the initially increased level of anxiety in the general population already during the first lockdown from 20 March to 16 April to 1.9 [9], in the further course of the pandemic until July stable, very slightly decreasing level to 1.70 and 1.66 respectively (taken from graphical representation) [7,8] Decline in all population groups, strongest among young people [9] c Depressive symptoms from Unchanged in OP compared to CP for older people and people with low income

Description and interpretation by authors of the publication Data basis: Study of the Universities of Mainz and Leipzig
Survey study (personal interview) using the random route method in the general population aged 14-95; temporal comparison with analogue study conducted in 2018

Outcome
Operationalisation Mental distress Single items Increase in the feeling of low mood in the general population(71% perceive second lockdown as depressing compared to 59% in the first lockdown compared to 36% in summer 2020) [17,18] Increase in severe family stress in the general population (25% in the second lockdown compared to 16% in summer 2020) [17] Increase in general population's perception that fellow citizens are inconsiderate (second lockdown 46% vs. first lockdown 40%) [17] Continued on next page

Data basis: Corona-COMPASS-Study
Survey study (online) with a random sample from a commercial panel (payback panel, no possibility for participants to selfselect); eligible population with online access aged 18

Outcome
Operationalisation/ measuring instrument Increase in the general population (in the study sites) to 8.8% (t2) compared to 6.4% (t1) and by an average of 0.3 compared to CP [27].

Description and interpretation by authors of the publication
Increase is only seen in persons under 60 years of age in the mean difference of 0.38+/-0.02 points [26]; clearest increase in youngest age group; stronger in regions with higher incidence and in persons tested positive for COVID-19 [26] c Symptoms of generalised anxiety disorder GAD-7 Cut-Off: >9 Total; mean difference to t1 Increase in the general population (in the study sites) to 5.7% (t2) compared to 4.3% (t1) and 0.45 for women and for men 0.2 [27] Increase is only seen in persons under 60 years of age in the mean difference of 0.38+/-0.02 points [26]; clearest increase in youngest age group; stronger in regions with higher incidence and in persons tested positive for COVID-19 Psychosocial stress burden

PHQ-D stress module
Total; mean difference at t1 Increase in the general population (in the study sites) in the mean difference by 0.36+/-0.02 points in all age groups [26] Increase stronger in regions with higher incidence and in individuals who tested positive for COVID-19 [26]

Outcome
Operationalisation/ measuring instrument Identification of three subgroups when analysing intra-individual changes: continuous increase in psychological symptoms at around 8%; at 9% initial increase and rapid decrease; at 83% improvement or unchanged from pre-pandemic levels [29,32]

Data basis: Longitudinal study (project to classify the factorial structure of protective factors influencing health at Saarland University)
Survey study (online), sampling from self-recruiting WiSo panel (sampling procedure not documented in publication); participants aged 20-95 years (M=55.0; SD=13.9), 53.6% female; comparison over time between t1 (before pandemic outbreak) and t2.

Outcome
Operationalisation Decrease in sample from 31.0% (t1) to 22.6% (t4) [28] Continuous decrease in the mean value of the sample across all measurement points; especially decrease in symptom severity; decrease in the median value from 4 (t1) to 3 (t4) [28] Intra-individual increase in about 25% of the sample from t1 to t4 [28] c Depressive symptoms PHQ-2 (Cut-Off >2); M, Median, Difference Decrease in sample from 32.7% (t1) to 25.3% (t4) [28] Continuous decrease in the mean value of the sample across all measurement points; especially decrease in symptom severity; no decrease in the median value [28] Intra-individual increase in about 25% of the sample from t1 to t4 [28] c Symptoms of generalised anxiety disorder GAD-2 (Cut-Off >2); M, Median, Difference Decrease in sample from 36.4% (t1) to 24.9% (t4) [28] Continuous decrease in the mean value of the sample across all measurement points; especially decrease in symptom severity; decrease in the median value from 2 (t1) to 1 (t4) [28] Intra-individual increase in about 10% of the sample from t1 to t4 [28] b COVID-19-related anxiety

C-19-A M, Median, Difference
Continuous decrease in the mean value of the sample across all measurement points; decrease in the median value from 9 (t1) to 4 (t4) [28] Intra-individual increase in about 10% of the sample from t1 to t4 [28] Continued on next page

Data basis: Online survey of the LVR-Klinikum Essen
Cross-sectional survey 1 (10.03.-27.07.2020): Sample composition differs from the general population at all evaluation points (approx: 70% female, 75% with high education (at least Abitur), 61% younger than 44 years). Standardisation by calculation of weighting factors for the distribution of characteristics in the general population is not described.
Since the second wave of infection, the study has been continued as a new cross-sectional study. 14.3% (OP) in sample vs. 7.6% (CP: retrospective assessment of instrument before pandemic); mean difference significant; interpreted as increase, especially among persons with pre-existing mental disorder [35] 14.3% (OP) in sample versus 5.6% (CP: norm sample); interpreted as increase [36] Lockdown 2 > Lockdown 1 in samples; interpreted as increase [34] Increase in sample from 8% in initial phase to 17% during phase 2 and 21% during phase 3 (crisis, lockdown), stable level afterwards; plus increase compared to 5.6% in pre-COVID-sample [38] c Symptoms of generalised anxiety disorder GAD-2 (Cut-Off >2), M 19.7% (OP) in sample vs. 9.0% (CP: retrospective assessment of instrument before pandemic); mean difference significant; interpreted as increase [35] c Symptoms of generalised anxiety disorder GAD-7 (Cut-Off >9, at least moderate symptoms) 16.8% (OP) in sample vs. ~ 6% (CP: norm sample); interpreted as increase [36] Increase in the sample over the course of the pandemic from 7% to 37% to 22%. Comparison with norm sample interpreted as up to 8-fold increase in prevalence in population exposed to COVID-19 [37] Increase in sample from 9% in initial phase to 22% each during phases 2 and 3 (crisis, lockdown), then slight drop to still higher level (22% and 20% respectively) compared to baseline values; plus increase in sample compared to norm sample of ~ 6%, interpreted as 2 to 10-fold increase in fear during pandemic [38] Unchanged in samples during the pandemic: lockdown 1=lockdown 2 [34] Continued on next page

Description and interpretation by authors of the publication b
Mental distress Distress Thermometer (Cut-Off >3) 65.2% (OP) in sample vs. 51.8% (CP: retrospective assessment of instrument before the pandemic); mean difference significant; interpreted as increase [35] 65.2% (OP) in sample vs. 39% (CP: norm sample); interpreted as increase [36] Unchanged in samples during the pandemic: lockdown 1=lockdown 2 [34] Increase in sample from 51% in initial phase to 63% during phase 2 and 60% during phase 3 (crisis, lockdown), then stable level of 58%; plus increase in sample compared to norm sample with 39% [38] b COVID-19 related anxiety Single item (Scale 1-7) Increase in sample at the beginning of the pandemic, then decrease below baseline level [37,38]

Data basis: CORA [see 28] Initial sample -Charité Berlin
Survey study (online; self-selecting) in general population 18 years and older; selective composition: 70.1% female; 82.4% higher education (at least university entrance qualification); comparison over time with norm sample before pandemic, adjustment of samples not described

Data basis: Initial sample of a longitudinal study of the University Tübingen
Survey (online; self-selecting) in general population aged 18-85 years with the aim of identifying protective factors for mental health; selective composition: 76.6% female; 81.4% higher education (at least university entrance qualification); comparison over time with representative pre-pandemic data without sample adjustment. [

Outcome
Operationalisation/ measuring instrument Particularly in women and in young people, the symptoms are more severe [45] Data basis: Online survey of the Universities Witten/Herdecke, ...

Description and interpretation by authors of the publication
Survey study (online, participant recruitment via snowball system); comparison over time by dividing the sample into three cohorts over the survey period    Telephone counselling (nationwide) [47] Reasons for contacting telephone counselling Central counselling topics for each contact to telephone counselling Telephone counselling (nationwide) [47] Journal of Health Monitoring 2021 6(S7) Contractual physician billing data from the Central Research Institute of Ambulatory Health Care in Germany [48] Outpatient diagnostic incidence and prevalence of anxiety disorders in GP practices Number of persons with (first) diagnosis of F41.0-3 or F41.8-9 Physician billing data from the practice panel of the Disease Analyser Database (IQVIA) [49] Outpatient diagnostic incidence of anxiety disorders in GP practices by age   Data about incapacity to work from AOK [64] Inpatient cases in psychiatric, psychotherapeutic and psychosomatic clinics and departments Number of treatment cases in specialised hospitals or departments for psychiatry and psychotherapy, child and adolescent psychiatry and psychotherapy, and psychosomatic medicine and psychotherapy that bill according to the PEPP system Data about incapacity to work from AOK [65] Day-clinic and inpatient admissions per day Number of admitted cases to day-clinic and inpatient care (planned admissions and emergencies) per day in clinics for psychiatry, child and adolescent psychiatry, psychosomatic medicine, geriatrics and addiction treatment LVR clinics inpatient care data [66] Day-clinic and inpatient cases by diagnosis Discharge diagnosis according to main diagnosis groups LVR clinics inpatient care data [66] Journal of Health Monitoring 2021 6(S7)